2 citations · 5 across the 5 of their papers we have counts for
5 papers
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
Jiahua Rao, Jiancong Xie, Hanjing Lin +3
Graph Neural Networks (GNNs) have gained considerable traction for their capability to effectively process topological data, yet their interpretability remains a critical concern.…
Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction
Zhiguang Fan, Yuedong Yang, Mingyuan Xu +1
The embedding of Biomedical Knowledge Graphs (BKGs) generates robust representations, valuable for a variety of artificial intelligence applications, including predicting drug comb…
Efficient Low-rank Backpropagation for Vision Transformer Adaptation
Yuedong Yang, Hung-Yueh Chiang, Guihong Li +2
The increasing scale of vision transformers (ViT) has made the efficient fine-tuning of these large models for specific needs a significant challenge in various applications. This…
EC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant Consistency
Zhiguang Fan, Yuedong Yang, Mingyuan Xu +1
Despite recent advancement in 3D molecule conformation generation driven by diffusion models, its high computational cost in iterative diffusion/denoising process limits its applic…
Leveraging Large-scale Computational Database and Deep Learning for Accurate Prediction of Material Properties
Pin Chen, Jianwen Chen, Hui Yan +6
Accurately predicting the physical and chemical properties of materials remains one of the most challenging tasks in material design, and one effective strategy is to construct a r…